Although LLMs have been around since the 1950s, let’s start by defining what they are. A Large Language Model is a type of AI program that uses deep learning and machine learning to perform natural language processing (NLP) tasks. LLMs are trained on large amounts of data to understand and generate human language.
LLMs are built on transformer models (because of the massive datasets they are trained on), which are neural networks that use self-attention to learn context and detect relationships between elements in a sequence.
Marketing-focused LLMs are specifically trained on your data. The data you use to train can be your marketing content, campaigns, analytics, and customer data. These LLMs can ingest and train on large amounts of data.
LLMs and Generative AI aren’t going anywhere, these tools have been around for a while, and they will continue to make an impact on multiple industries. Across those industries and companies, Gen AI is being utilized to create content (like social posts, ad copy, and blogs), creative assets, templates, product descriptions, and metadata to create efficiencies in their marketing and creative teams as well as improve speed to market for test iterations.
In a recent Web FX poll, 50% of the 200 senior marketing and Sales leaders surveyed are using AI in their marketing strategies.
Let’s dive into specific use cases.
Over half of marketers (55%) in an eMarketer study use AI for content ideation, indicating the technology’s value in generating new creative concepts and strategies. Let’s look at some examples of how a Marketing LLM can impact your campaign creative:
In the same eMarketer study from earlier this year, almost half (45%) of the respondents use AI to gather consumer insights, showcasing AI’s role in understanding market trends and customer behaviors. Marketing LLMs can deliver value with:
There are clear differences between chatbots and conversational AI. Chatbots use predefined conversation flows that are limited. Think about the last chatbot you used—there are clear limits to what it can answer based on your input. Simply put, Conversational AI uses machine learning and NLP to provide a more robust, personalized experience. There are use cases for both – broadly they can be used for:
Testing your marketing is critical to increasing its effectiveness, reducing waste on strategies that don’t work, and increasing the ROI of your campaigns – Marketing LLMs are a great tool to help you with all of that.
Marketing LLMs can have an impact on Marketing automation – from identifying prospects that can convert to finding the best time to market to them to get that conversion. They can also assist in:
In 2017, The Economist declared that data was the most valuable resource. Although the article focused on US tech companies and their use and storage of massive amounts of data – it’s a very relevant topic for AI and Marketing LLMs.
Data quality and privacy concerns are top considerations when using a Marketing LLM – the data the system is trained has a direct impact on the results. Poor data quality can quickly cause issues with an LLM. These issues can be mitigated before they even start by:
Privacy concerns: You need to ensure that training data does not contain personally identifiable information (PII)—if it does, it increases the risk of being exposed by hackers and is subject to multiple laws worldwide. The best policy regarding privacy concerns with PII is to ensure that data is anonymized and that consent is obtained where necessary.
Ethical and responsible AI implementation: We’ve all seen the news stories about bias and discrimination in LLMs, and it’s clear that improved data quality and human oversight are critical to preventing bias, discrimination, and misleading information that can hurt historically marginalized communities.
As LLMs continue to evolve, we can count on a future with them making an impact on both consumers and businesses. Advancements in LLMs will include a deeper level of personalization, advanced conversational capability, and an industry-level focus on specific industries.
Today, LLMs can provide businesses with a clear advantage by enhancing productivity by optimizing operations, reducing costs, and improving delivery. LLMs can process and analyze vast amounts of data faster and more efficiently than people, driving quicker, more accurate decision-making.
When it comes to Marketing LLMs, there are so many practical applications that can uplevel your marketing and customer experience for your customers—and these capabilities will only grow as new LLMs enter the marketplace.
Although there are some clear concerns about data quality, potential biases, and privacy, these can all be mitigated by strong controls (process and procedure) combined with actual human oversight.
We believe there’s a clear competitive advantage to using Marketing LLMs and that the benefits clearly outweigh the concerns.
